Modelling and valuation of catastrophe bonds across multiple regions
By: Krzysztof Burnecki, Marek Teuerle, Martyna Zdeb
Potential Business Impact:
Helps predict big disaster costs for insurance.
The insurance-linked securities (ILS) market, as a form of alternative risk transfer, has been at the forefront of innovative risk-transfer solutions. The catastrophe bond (CAT bond) market now represents almost half of the entire ILS market and is growing steadily. Since CAT bonds are often tied to risks in different regions, we follow this idea by constructing different pricing models that incorporate various scenarios of dependence between catastrophe losses in different areas. Namely, we consider independent, proportional, and arbitrary two-dimensional distribution cases. We also derive a normal approximation of the prices. Finally, to include the market price of risk, we apply Wang's transform. We illustrate the differences between the scenarios and the performance of the approximation on the Property Claim Services data.
Similar Papers
Design and valuation of multi-region CoCoCat bonds
Pricing of Securities
Insures against many disasters at once.
Unveiling Nonlinear Dynamics in Catastrophe Bond Pricing: A Machine Learning Perspective
Computational Finance
Prices risky insurance bonds more accurately.
Machine learning models for predicting catastrophe bond coupons using climate data
Pricing of Securities
Predicts disaster bond prices using weather patterns.